- author = "Seishi Takamura and Atsushi Shimizu",
- title = "Concurrent Evolution of Pixel Predictor and Context Modeling for Image Coding",
- booktitle = "2016 IEEE International Conference on image Processing, ICIP",
- year = "2016",
- editor = "Fernando Pereira and Gaurav Sharma",
- pages = "2147--2151",
- address = "Phoenix, Arizona, USA",
- month = "25-28 " # sep,
- organisation = "IEEE Signal Processing Society",
- keywords = "genetic algorithms, genetic programming, Cartesian genetic programming, image coding, pixel predictor, context modelling expression: Poster",
-
URL = "
http://2016.ieeeicip.org/Papers/viewpapers.asp?papernum=3228",
-
DOI = "
doi:10.1109/ICIP.2016.7532738",
- size = "5 pages",
- abstract = "Lossless image coding process predicts the value of current pixel from previously decoded pixel values. Then the prediction error is classified according to the context model. This classification splits the sources with different distributions and hence reduce the total entropy of the prediction error signals. In the literature, the predictor has been intensively studied. Some evolutionary approaches have been applied to generate a predictor to improve compression performance. However, the context modelling method has not relatively been well studied. We propose and investigate a novel method to automatically obtain evolved pair of pixel predictor and context modeling. Simulation results show 1.32-3.90percent bit-rate reduction against the pair of predictor and context modeler of one of the best conventional methods (CALIC). It is also demonstrated that the evolved algorithm's size is more compact than former results. We also found that context modeler is evolved in more complex form than the predictor.",
-
notes = "ICIP 2016 Image and Video Coding. paper MPA-P3.3
NTT Corporation",
